Vasso Papadimitriou | Engineering | Best Researcher Award

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Ms. Vasso Papadimitriou | Engineering | Best Researcher Award

Aristotle University of Thessaloniki | Greece

Ms. Vasso Papadimitriou is an accomplished researcher and academic affiliated with the Aristotle University of Thessaloniki and the Region of Central Macedonia, Greece. Her research primarily focuses on construction project management, cost estimation models, and the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques, particularly Artificial Neural Networks (ANNs), in the field of building renovation and project planning. She has contributed significantly to the development of predictive and hybrid models that enhance accuracy in early-stage and final cost estimation for construction and renovation projects. Dr. Papadimitriou’s innovative work combines ANN methodologies, including Radial Basis Function (RBF) and Multilayer Perceptron (MLP) networks, with Multi-Criteria Decision-Making (MCDM) approaches such as the TOPSIS Methodology to create efficient, data-driven tools for project assessment and optimization. Her research also aligns with Sustainable Development Goals (SDG 9 and SDG 17), focusing on promoting innovation, infrastructure, and partnerships for sustainable growth. She has published in international peer-reviewed journals indexed in Scopus, Web of Science (SCI-Expanded, ESCI), and other scientific databases. According to Scopus, she has 6 publications, 3 citations, and an h-index of 1. On Google Scholar, she holds 14 total citations, an h-index of 3, and an i10-index of 1, while ResearchGate records 6 publications, 11 citations, and an h-index of 2. Her interdisciplinary approach bridges civil engineering, computer science, and digital construction, contributing to advancements in cost modeling and sustainable infrastructure management. Through her publications and research collaborations, Dr. Papadimitriou continues to make impactful contributions to the field of engineering innovation and AI-driven construction technology. Her outstanding achievements and innovative contributions to predictive modeling and sustainable construction management make her a deserving nominee for the Best Researcher Award.

Publication Profile

Scopus | Google Scholar

Featured Publications

Papadimitriou, V. E., & Aretoulis, G. N. (2024). A final cost estimating model for building renovation projects. Buildings, 14(4), 1072.

Papadimitriou, V. E., Aretoulis, G. N., & Papathanasiou, J. (2024). Radial Basis Function (RBF) and Multilayer Perceptron (MLP) comparative analysis on building renovation cost estimation: The case of Greece. Algorithms, 17(9), 390.

Papadimitriou, V., & Aretoulis, G. (2023). Neural network models as a cost prediction tool to prevent building construction projects from a failure—A literature review. Proceedings of the Erasmus+ PROSPER Project International Scientific Conference, 1–10.

Papadimitriou, V. E., & Aretoulis, G. N. (2025). An innovative approach regarding efficient and expedited early building renovation cost estimation utilizing ANNs and the TOPSIS methodology. Algorithms, 18(11), 696.

Kritikos, P., Papadimitriou, V., & Aretoulis, G. N. (2021). Required project designers’ attributes as perceived by male and female engineers. International Journal of Decision Support System Technology (IJDSST), 13(4), 1–15.

 

 

Qiusong Liang | Engineering | Best Researcher Award

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Ms. Qiusong Liang | Engineering | Best Researcher Award

Northeast Forestry University | China

Ms. Qiusong Liang is a promising mechanical engineering researcher whose work focuses on advanced simulation, optimization, and design of electro-hydraulic and electromechanical systems. Her research emphasizes multi-objective optimization, structural dynamics, and fluid–structure interaction analysis to enhance the performance and reliability of servo and direct-drive valve mechanisms. She skillfully integrates computational tools such as ANSYS, SolidWorks, Maxwell, and AMESim for high-precision modeling and simulation, contributing significantly to innovations in flow control mechanisms, torque motor optimization, and cavitation noise reduction in hydraulic systems. Her recent studies explore the dynamic characteristics of torque motors and the coupling effects between electromagnetic and fluid systems, leading to improved high-response servo valve technologies for industrial and military applications. Ms. Liang’s research excellence and innovative approach have been recognized through publications in internationally indexed journals and notable contributions to engineering design projects. She maintains an active research profile with Scopus- and Google Scholar–indexed publications, accumulating documented citations and a growing h-index that reflect her rising academic influence in the field of mechanical system optimization and applied simulation engineering. Her commitment to applied research, precision design, and interdisciplinary collaboration has earned her recognition as a recipient of the Best Researcher Award, highlighting her as one of the emerging leaders in smart mechanical systems and sustainable automation technologies.

Publication Profile

Orcid

Featured Publications

  • Zhang, J., Liang, Q., Sun, J., Yan, B., Hu, Z., & Sun, W. (2025, October 29). Multi-objective optimization of torque motor structural parameters in direct-drive valves based on genetic algorithm. Actuators, 14(11), 527.

Yair Rivera | Engineering | Best Researcher Award

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